fabriziomusacchio Goto Github PK
Name: Fabrizio Musacchio
Type: User
Company: DZNE Research Center
Bio: Hello, my name is Fabrizio Musacchio and I love to play with pixels.
Location: Cologne, Germany
Blog: fabriziomusacchio.com
Name: Fabrizio Musacchio
Type: User
Company: DZNE Research Center
Bio: Hello, my name is Fabrizio Musacchio and I love to play with pixels.
Location: Cologne, Germany
Blog: fabriziomusacchio.com
A how-to for building an artificial neural network from scratch using NumPy
Scripts for evaluating common Python image registration methods
Generates a table of contents and Back-to-top links in DEVONthink's Markdown documents.
A collection of Applescripts for processing images in DEVONthink
Code used in blog post about dimensionality reduction using Python
The code in this repository is modified after scipython.com. It plots Earth's dipolar magnetic field and was used in the blog post on Earth's dipolar magnetic field. For further details, please refer to this post.
This repository contains the code for the blog post on Understanding entropy. For further details, please refer to this post.
This repository contains the code for the blog post on The Weistrass function and the beauty of fractals. For further details, please refer to this post.
A GitHub flavored Markdown Style Sheet (CSS)
This repository contains the code for the blog post on Understanding gradient descent in machine learning. For further details, please refer to this post.
Python scripts supporting a tutorial on the Hodgkin-Huxley model.
In this tutorial, we explore the mathematical underpinnings of Hebbian learning within Hopfield networks, emphasizing its role in pattern recognition.
Python scripts supporting tutorials on Izhikevich neuron model.
This repository contains the code for the blog post on Understanding L1 and L2 regularization in machine learning. For further details, please refer to this post.
This repository contains the code for the blog post on Solving the Lorenz system using Runge-Kutta methods. For further details, please refer to this post.
This repository contains the code for the blog post on The Lotka-Volterra equations: Modeling predator-prey dynamics. For further details, please refer to this post.
This repository contains the Python code my blog post Image denoising techniques: A comparison of PCA, kernel PCA, autoencoder, and CNN. See post for more details and results.
This repository contains a HTML script including liquid commands and JavaScript, that integrates a Mastodon-powered comment system into a static website. The script is written in a way that it can be used with the static site generator Jekyll.
Workshop for scientific programming and data analysis in MATLAB
Image data and Python scripts for the course on Bioimage analysis with Napari
Deconvolution of calcium imaging data
This repository contains the code for the blog post on Runge-Kutta methods for solving ODEs. For further details, please refer to this post.
Python scripts supporting tutorials on phase plane analysis.
This is the course material for the introductory course into Python basics for Data Scientists.
This is the course material for the advanced course into Python for Data Scientists.
A collection of script for basic performance tests in Python.
Code used in two blog posts on decision trees and random forests.
Example on how to read patch clamp recordings in WaveMetrics IGOR *.ibw files.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.